1. Field
The present invention relates generally to communications networks, and more particularly to self-optimizing networks.
2. Description of Related Art
As demand for wireless access to the Internet and Internet-based services is expanding, competitive advantages in the mobile business can be gained by offering enhanced user experience through cost effective broadband mobile access. A promising approach is to maximize total performance of networks, i.e., provide not only wireless access with higher performance but also more efficient operation and maintenance. The Self Optimizing Network (SON) introduced as part of the 3GPP Long Term Evolution (LTE) is one approach for improving wireless networks. It aims to reduce the cost of installation and management by simplifying operational tasks through automated mechanisms such as self-configuration and self-optimization. The challenge faced by mobile operators is to ensure that mobile services are of a high quality while reducing capital expenditures and operational expenditures of complex radio access networks (RANs). Using an SON can remove several human interventions from network operations and maintenance.
Self-optimizing and self-healing architectures improve user perceived qualities by mitigating quality degradations that result from inaccuracies of the planning or equipment faults as early as possible and by optimizing the network parameters under interference and overload conditions.
One area of particular interest for SONs is that of interference management. In addition to one or more evolved Node B (eNodeB or eNB) (also known as macro cells) within the network, typical SONs can also include Home eNBs. Introducing home eNodeBs (also known as femtocells) significantly increases the number of base stations in the network and it also means that the network operator has less control of the nodes. Therefore, there is a need for self-configuration of home eNodeBs. For example, a major challenge is the interference between home eNodeBs and macro cells and interference between home eNodeBs in close proximity to each other. Therefore, there is a need to authenticate and identify the location of the home eNodeB before authorizing it to transmit in the licensed radio spectrum. The home eNodeBs also sniff the configuration information broadcast by the surrounding macro cells, and select appropriate physical cell IDs, location area IDs, etc.
In a heterogeneous network such as this, a mobile user device (UE) cannot always simply move to a cell with the best channel characteristics. Thus there remains a need, currently unmet by the present art, to provide interference management easily and effectively within a SON environment.